SECAI Core · phase 1 of 15
Unsupervised learning
A category of machine learning that does not use labeled data to predict outcomes, but instead relies on the computer to sort out patterns and similarities in the larger dataset.
The Explain card
- Plain English
- Unsupervised learning gives the machine data without labels and lets it find the patterns, groups and similarities on its own.
- Example
- A security team feeds raw authentication logs into a clustering algorithm. It groups logins into natural clusters, and one small odd cluster turns out to be a service account being used from three countries at once.
- Why it matters
- Unsupervised models surface what is unusual, which makes them great for anomaly detection, but they also find patterns nobody asked for, including sensitive groupings that raise privacy and bias questions.
- Hook
- No answer key, just "sort this pile and tell me what looks odd."
Where it sits in the deck
Phase 1: What AI Is: Core Concepts and Paradigms
You cannot secure, govern, or attack something you cannot define — establish what AI actually is before any other concept can land.
